{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b7500b1d-d16d-40f2-a8f2-e1b64f382ab7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Patch\n",
    "import numpy as np\n",
    "from matplotlib.patches import Patch\n",
    "from matplotlib.font_manager import FontProperties\n",
    "\n",
    "import matplotlib as mpl\n",
    "from matplotlib.lines import Line2D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "cacdeba1-91d1-48d3-9c4a-daaee4568cc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "ar = pd.read_csv('./ar_subjectivity_250210.csv')\n",
    "al = pd.read_csv('al_subjectivity_250210.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a8f13039-aeb7-4274-b952-9573ebeeb013",
   "metadata": {},
   "outputs": [],
   "source": [
    "boxplot= [al.Subjectivity, ar.Subjectivity]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "6726675f-b245-471d-a35d-565e9b03325d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/liuanqi/opt/anaconda3/lib/python3.8/site-packages/matplotlib/cbook/__init__.py:1376: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
      "  X = np.atleast_1d(X.T if isinstance(X, np.ndarray) else np.asarray(X))\n"
     ]
    },
    {
     "data": {
      "image/png": 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M3bp1kyTNnDmzWjHH1p82bVq1br+TOOBTTXTv3l177bWXnnrqKa1atarSk/cOHTqoefPmeuONN7Rhw4Ya7QOZq2nTppIUTxxbtGghSUl7O7z99tspy0r2Gfnss8/0xRdfqLi4uNLWW0nafvvt1bFjR3300UdasWJFtWKPfUamTp1arfXr1atX48+HFCS49erV07hx47RhwwZNmDBBO+20U7kuy4nxVPczni1IcAEAADLM7rvvrssvv1wbNmzQCSecoP/+979brPPkk09qxIgRysvL01133bXFda8vvfSSnnnmmXKv3X777fr000/Vq1evKkelPf/885Wfn6+LLroo6S1b1q9fX+7EuEuXLjrssMM0Z84c3XjjjVus/80335S79UpsMKiKtxqqjiFDhuiHH37QnXfeqX//+9864IADtkjY69evrwsuuEBfffWVLrzwQq1bt26Lcr766qukdYvoTJgwQc8//3zSH0lKS0vjt6054ogjJEkHH3ywpM231or54osvdM0116Tc1+jRo8sNtrZp0yZdfPHF2rRpk84444wqY/3DH/6g9evXa9iwYUlbi1euXKl33nkn/nzIkCHaYYcddNddd+nll1/eYv3YKMoxO+64Y7UuU6ioXbt26t27t9544w2NHj1ay5cv36KHgyR17dpVPXr00OOPP17poFoffPCBli2rfNT4TMQ1uAAAABlo5MiRWrt2rf7+97/rwAMP1DHHHKOOHTtqw4YNeu211zRr1iw1atRIEyZMKHd7oJhf/vKX6tevn/r166c999xTc+bM0dSpU9WyZUvdeeedVe6/Q4cOGjNmjIYNG6aOHTvq2GOPVfv27bVhwwZ9/vnnmjlzplq1aqV58+bFt3n44YfVs2dPXX755Zo0aZJ69uwpd9eCBQv03HPPad68eSouLpYUjMT82GOP6aSTTtIvfvELNWrUSLvuuqsGDx5cZWyDBw/W//7v/+qqq67Shg0bKr2f7ZVXXqn33ntPd999tyZPnqzevXurqKhIy5Yt04IFC/Tqq6/q+uuv17777lvlPlE3Zs2apdGjR6ugoECHH364dtttN0nBPZanTJmidevW6Ve/+pVOPvlkSdIhhxyiI444Qi+//LIOPvhg9e7dW0uXLtXkyZN1zDHHpEwQu3fvrk6dOunUU09Vs2bNNG3aNL333nvq0qWLLrnkkipjHTZsmGbPnq0777xTe+yxh4455hjtsssuWrFihRYuXKiXX35ZZ5xxhu6++25JwUji48eP18knn6xevXqpb9++OuCAA7R69Wq9//77+uKLL8p1me/Tp48effRR/fKXv1Tnzp2Vn5+vI444Ip7cpzJkyBC98MILuvzyy+PPkxk/frx69+6tM888U//4xz90yCGHqHnz5vryyy/1/vvv68MPP9Trr7+u1q2zaIyOqvqMMzElmyQVSnJJvmTJEgeQG/7+/MfxCdXzxehb4xNqR5cuXaIOIaPMmjXLTz/9dC8uLvaGDRt6kyZNvGPHjv7HP/7Rv/jiiy3WHzt2rEvysWPH+uTJk71bt27euHFjb9asmZ900kn+8cdbfr6HDBniknzhwoVbLHv//fd9yJAhvssuu/h2223nLVq08I4dO/rw4cP9xRdf3GL9r7/+2i+55BJv3769N2jQwJs1a+YHHnigX3755b527dr4ehs3bvTLLrvMd9ttN69fv75L8iOPPDK+fNddd/Vdd9210nrp06ePS/L69et7aWlppett2rTJH3zwQe/du7e3aNHC8/PzvbCw0Lt37+7XX3+9f/7555Vui7r3+eef++233+4nnniit2/f3ps2ber5+fleUFDgffv29YceesjLysrKbbNy5Uo/66yzvFWrVr7ddtt5x44d/Z577vGFCxe6JB8yZEi59WPH+6effup//etffe+99/YGDRp4YWGhjxgxwletWrVFXKmOx8mTJ/txxx3nrVq18vz8fG/Tpo3/7Gc/8yuuuMLnzp27xfoffvihDx482AsLCz0/P99bt27tRxxxhN9zzz3l1lu6dKmfdtpp3rp1a69Xr55L8quuusrdvdL3FrN27VrfYYcdXJLvt99+ySs7tHr1ar/++uu9c+fO3qRJE2/YsKEXFxf7L37xC7/nnnv8u+++S7l9TGXf3UuWLPFY3iCp0NOcp5i7b5n1AlUws0JJS6TgQvmKIzcCyE7Fl02Jzy8adVyKNREza6894/OHLPgkwkhyR9euXau8dg61a+DAgZo4caJKSkq08847Rx0OkHEKCgrUrFkzffzxx1GHkrEq++4uKSlJHDm6yN1LtlipFnENLgAAwE/c/Pnz1aBBA7Vq1SrqUICMs2LFCn399ddq27Zt1KGgGrgGFwAA4Cdq9OjRmjFjht59910NGDBA9etzagjErFq1Sn/96181bdo0lZWVxa/7RWbjWwwAAOAn6tZbb42PAvu3v/0t6nCAjLJy5UqNGjVKu+22m0aNGqWzzz476pBQDSS4AAAAP1GJI7YCKK+4uLjcrYeQHbgGFwAAAACQE0hwAQAAAAA5gQQXAABknE2bNkUdAgCgmjLpO5sEFwAAZJSWLVuqtLQ06jAAANVUWlqqli1bRh2GJBJcAACQYXr06KGpU6dGHQYAoJqmTp2qHj16RB2GJEZRBgAkOO1n7aIOIeu0OvXUqEPIOYMHD47fjqNv374qKChQvXr8Jg8AmWTTpk0qLS3V1KlT9a9//Uv33HNP1CFJkszdo44BWcjMCiUtkaQlS5aosLAw4ogAALlk0aJFeuihhzRz5kytWLEi6nAAAEm0bNlSPXr00ODBg1VcXJx0nZKSEhUVFcWeFrl7STpjIsHFViHBBQAAAFCVuk5w6e8DAAAAAMgJJLgAAAAAgJzAIFMAgLjLHn8/Pj/qpAMijCR7fPbnK+Lzu193fYSRAAAAElwAQNyEt76Iz5PgVs/yiRPj8yS4AABEiy7KAAAAAICcQIILAAAAAMgJJLgAAAAAgJxAggsAAAAAyAkMMgUAyBpr167VvHnzJEkdOnRQkyZNIo4IAABkEhJcAIjAvffeq/Hjx0cdxpYOvTg+27Nnz+jiqMSaNWv0zjvvSJI6d+6spk2bRhyRdGPCfCbWWVUGDRqk4cOHRx0GAAC1gi7KABCB8ePHa86cOVGHgZ+4OXPmZOYPLQAAbCVacAEgIp06ddL06dOjDqOc4sumxOczLTZJmj17trp27SopaAXv0qVLxBFJs/baMz6fiXWWSja2OAMAkAotuAAAAACAnEALLgAgbkSfvaIOIesUXXBB1CEAAIAQCS4AIO6io9pHHULWaXvhiKhDAAAAIbooAwAAAAByAgkuAAAAACAnkOACAAAAAHIC1+ACAOLOHPdWfP6fQ34WYSTZ4+Phv43P733vfRFGAgAASHCRNcrKyrR06VJJUps2bZSXlxdxREDueXHesqhDyDrf/uc/UYcA4CeE8yEgNbooI2ssXbpURUVFKioqin+xAwAA/JRwPgSkRoILAAAAAMgJJLgAAAAAgJyQcwmumfU0MzczjzoWAAAAAEDdiSTBNbMWZrYuloia2V5RxAEAAAAAyB1RteD+WlLDhOfDIooDAAAAAJAjokpwzwwfbwsfh5gZY5wDAAAAALZanSe4ZtZZUidJ30q6RNJCSTtL+kVdxwIAAAAAyB1RtODGWm8nuvsPkh4Mn6fspmxmD4TX6z5ggbPM7BUz+yZ8fWh1dm5mO5rZ6+E2C82sfcKybmZ2o5nNNLPFZvaDmX1rZm+Y2f+Y2fYpyo1dT9zTzJqa2XVmNi+81vgbM3vGzA5JsX0LM7vGzN4xs9Vmtt7MSs3sfTO728z6JNlmtzCuZ81svpmtNbPvzOy/Znarme1SRV2camZTzWypmW0I3+sCM3vazM4zs4aptgcAAACATFK/LncWJkyDwqcPJjz+r6TjzayNu1d1x2qT9Jik/pI2SVoVPlZn/7tKelZSB0nvSerr7l8lrPJ6wvz34dRC0iHhdLqZ9XL3ZSl2s7OkdyTtKemHMLaWko6T9HMz+6W7P1chrraSXpUUS0hj72snSW0k7R/G/GKFfY2VdGQ4v17SmjDefcJpqJkd7+6vJKmLMZLOSHjpO0n5Ydx7SvqlpCmSFqV4rwByzF/67R91CFlnt2uvizoEAAAQqtMEV0FS2lzSJ+7+miS5+2dm9oqkHpJOl3RzFWWcpGCAqj9Jus/dV4ctq01TbWRmB0iaKqlQ0n8knejuqyusNlnSw5JedvfScLtGko6VNErSvpLuDmOozB2SvpLUW9IMSS6pq6SHJO0t6V4z293dE5PykQqS20WSzpI03d3LwuuS20rqK6k4yb7mSPqXpOclferum8ysvqTOkq4O455oZnu6+7qEujhcQXK7SdJlku539xXhsh0ldVHwQ8T6FO+zzpWVlcXnS0tLI4wE2HY//vijpOC4zsvLnCEIBh2csuMHkmg9cGDUIWyVsrKy+HFYUlIScTQAqivxHCjx3AhAoK4T3Fj35AcrvP6gggR3mKpOcLeXdKG7xwaokrt/p6AFMikzO1LSU5KaKWj9HezuP1Zcz91PSPLaOklPmNmbkj6VdKKZ7eLun1eyu42SKrbyvmVmp0h6X9Kukg5V0GIbc1j4eLm7x1tp3b1M0mIFSfUW3P33SV7bKOlNMzteQUvyAQp+WHg4yf5ecPebKmz/jaTnwimjLF++PD7fpUuXCCMBas/SpUtVWFgYdRj4CVq6dKneeOMNSVJRUVHE0QDYGsuXL1e7du2iDgPIKHV2Da6Z7S6pp4IWzYcqLP6XpHWSOpjZYUptpaR7arDfkyVNU5Dc3i5pYLLktiruvkRBt2bT5gQxmXuTdWF29w8UDKglBUlnom/Dx51rGldlwuT42fDp4ZXsr9XWjF5tZsMVtIYDAAAAQMaoyxbcMxQkhy+7+6LEBWE34yclnaaglfe1FOW85e7V6jprZudJ+oeCRP4Kd/9LFevXkzQwnDpJaqXy9+uNaZuimFkplpVI2k3BNbmJnlHQqnuDmXWQ9Lik15J0oU4Wcw8FddYtjKtJNeJ9UcH1wQdJmmlm/5T0krsv3GLLJNz9XjN7RtKS6qxfW1q1ahWfnz17tgoKCupy90Ct6t+/vySpTZs2EUeCn6o2bdqoW7dukqRJkyZFHA2A6iotLY33ZEs8NwIQqJMEN0wch4ZPK3ZPjhmnIMEdYGYjwm7HyaQa4Kmi28PHO6qR3DZWkGj2Snh5vaQVkjaEz1sqGIgpWRIZsybFso3hY36F12+WdKCkAZJ+G05uZh8paIW9390/ThLzjQputRRTpqCFO/YDwPZhrOXidfdPzewsBV2fDw0nmdlyBdcnj5f0tLt7ivdS5xKvUywoKKBbJ7JagwYNJCmjrr+VpONvmxmff+aCHhFGkj0+OPFX8fn9n3wqwkhqJi8vL34c8n0KZKdM+x8CZIK66qJ8jDa3It6fcEud+KTN3Wm3V5DoVaYmV9PHrjv9rZn9sop1r1CQ3K6TdJGCa2UbuvuO7l7g7gXa3DprNYihSu6+wd1PVdBqfI2klxSM4LyfgsG0PjKzPyZuY2Y/1+bk9k4FIy03cPeWCfHeUlm87v5I+B7PkTRR0hcKWqwHSHpS0gwz26E23yeAzPdhyer4hOr5/qOP4hMAAIhWXSW4Z1a9yjatX5khClqGt5M0ycxOTLFubBjMa9z9Vnf/PEkLZlr7xLr7e+5+lbv3UTDa9FGSXpaUJ+lmMzswSbzT3P08d/8wvO622vG6+wp3v8fdB7r7LgpuD3SDguukeygY3RkAAAAAskLaE1wzayUpNjrxyQpu51PZdHC43mFmtve27ju8Fc8wSWMUdAv+l5n1r2T12BB07yZbaGbFChLAOuHuG8MRlY+T9KOCVtijElapKl5TcKuimuzzU3e/TEEXZUn6eY2CBgAAAIAI1UUL7mAFyeUqSZPd/bsU01uS5oXb1UorbpjkniXp3jCOR80sWRfoVeHjgUmWSUHLZlqYWYMUi3/U5m7ZiffOrSrecyTtvhX7k4Ju2hX3BwAAAAAZrS4S3Fii+lQ1Rz9+LHw83cxqZRCssKvxOQquVa0vabyZnVZhtdg1wH82s5Ni+zaz3cxsvIJrU1fWRjxJLDazURjIK7IAACAASURBVGbWLTH5NLM9JT0iqbGCZHNaknj7mtmVZtYk3Ka5mV0u6TZJ31Syv9vN7F9m1t/MWifsb3szO0fS6eFLU2rl3QEAAABAHUhrgmtm3STtGz59LNW6CWLrtVHQPbdWeOA8BYlfnqSHzOw3Cav8WdJSBV2lJ0laZ2bfSvpMwejOV0h6v7biqaCNpEslvS7pezNbYWbrJC2QdIqCa2L/6O7/TdjmQUmx4U6vkbTGzFYoSGqvV5AA31XJ/vLDcv9P0lIzW2NmKxWMAH2XgmuWXwnLAQAAAICskO4W3Fjr7SpJz1VnA3f/QNLcCtvXGne/UMHownmSxpnZ0PD1xZK6SvqngvvVSsG9Yp+RdIy7j6rtWBIcLWmUgoT1C0mNwtc/kTRW0s/c/dYK72NDuN3VkuYruJWRSXpT0rkKrnuubMTpayVdKOkJBV3CNyoYvXqZpOcVXLfc093X1s7bAwAAAID0S+t9cN09dk/Xmm63b5LXhmrzvXRTbTtdVdzGx93/IOkPSV7/UsH1upVt1zPFsipvHVTZ9u7+vILEskbc/QcFIx2PrGSVpMvc/VMFLdm31XSfAAAAAJCp0prgArWpTZs2WrJkSXweAADgp4bzISA1Elxkjby8PBUWFkYdBgAAQGQ4HwJSI8EFAMTdf3rXqEPIOu3vvifqEAAAQIgEFwAQd9Q+dHerqRZ9+kQdAgAACNXFfXABAAAAAEg7ElwAAAAAQE4gwQUAAAAA5ASuwQUAxB38lxfi829eflSEkWSPd7ofFp/v/OprEUYCAABIcAEAccvW/Bh1CFlnw7JlUYcAAABCJLgAEIEZM2ZIknr27BltIBUdenF8NuNik7RmzZr4/PDhw9W0adMIowncmDCfiXWWypw5c9SpU6eowwAAoNZwDS4AAD9RnTp10qBBg6IOAwCAWkMLLgBEwN2jDiGp4sumxOenT58eXSCVWLt2rebNmydJ6tChg5o0aRJxRNKsvfaMz2dinQEA8FNCggsAyBpNmjRRly5dog4DAABkKLooAwAAAAByAgkuAAAAACAnkOACAAAAAHICCS4AAAAAICeQ4AIAAAAAcgKjKAMA4iaff3jUIWSd/Z54MuoQAABAiAQXABC3f1GzqEPIOk322y/qEAAAQIguygAAAACAnECCCwAAAADICSS4AAAAAICcwDW4AIC44sumxOcXjTouwkiyx6y99ozPH7LgkwgjAQAAtOACAAAAAHICCS4AAAAAICeQ4AIAAAAAcgIJLgAAAAAgJ5DgAgAAAAByAgkuAAAAACAnkOACAAAAAHICCS4AAAAAICeQ4AIAAAAAcgIJLgAAAAAgJ9SPOgAAQOaYdVmfqEPIOge98mrUIQAAgBAJLgAgrs0ODaMOIets16ZN1CEAAIAQCS4AICutXbtW8+bNkyR16NBBTZo0iTgiAAAQNRJcAMgw9957r8aPHx91GBlvzZo1eueddyRJnTt3VtOmTSOOKLMNGjRIw4cPjzoMAADSikGmACDDjB8/XnPmzIlk3xvzm8QnVE/TsrL4lKnmzJnDjyYAgJ8EWnABIAN16tRJ06dPr/P9Fl82JT6/aNRxdb7/mpg9e7a6du0qKWj17tKlSyRxzNprz/j8IQs+iSSGqvTs2TPqEAAAqBO04AIAAAAAcgIJLgAAAAAgJ5DgAgAAAAByAgkuAAAAACAnkOACAAAAAHICCS4AAAAAICdwmyBkpbKyMi1dulSS1KZNG+Xl5UUcEQAAQHmcrwB1jxZcZKWlS5eqqKhIRUVF8X8cAAAAmYTzFaDukeACAAAAAHICCS4AAAAAICdk5TW4ZjZS0lWSZrh7z1osd6iksZIWu3txbZULANli0ajjog4h6xyy4JOoQwAAAKGMaME1sxZmts7MPJz2ijomAAAAAEB2yYgEV9KvJTVMeD4sqkAAAAAAANkpUxLcM8PH28LHIWbGOOoAAAAAgGqL/BpcM+ssqZOkbyVdIul4SbtJ+oWkyRGGBgA/OR8sWRWf37+oWYSRZI+1H34Yn2+y334RRgIAADKhBTfWejvR3X+Q9GD4fKu6KZtZYzM7zcweNLM5ZrbczH40sxIze9LM+tagrJ+b2dSwjHVm9pGZ/dnMGlayfr6ZnWBm95rZ22b2lZmtN7NlZjYtjMsq2bZn7Brk8PkBZjYhjHudmc01sz+ZWf2EbbqH7+krM/vBzD40s/NS7KPAzC4ws6fC8laFZX9iZvebWcfq1g2A3PTL21+JT6ieD/udGJ8AAEC0Ik1ww0RxUPj0wYRHl3S8mbXZimIHSBovabCkAyTlS9ooaWdJv5L0bzP7azVi+52kaZKOVdDSXV/SvpKulfSambVIsll3SU9J+q2kLpIaS/pBUitJR4dxTTSzlPUeJuGzJA0My2ggqYOkmyU9FK5zlqQZkk6Q1Chcp6Ok2yWNqqToGyT9I9xmTwX1Ul/SHgp+aJhtZv1TxQYAAAAAmSrqLsr9JTWX9Im7vyZJ7v6Zmb0iqYek0xUkdTWxUtJfJT0p6V13/16SzGxnBYnnnyX90cxedvenKymjlaRbJf2fpD+6+xdm1kjSkPD1gyT9U9JJFbb7XtI94XZvuvvqcN8tJf1GQXJ8iqRXFCSalRmvIFG+xN0/N7Omki4Lp4Fm9p6kayTdKek6d18WJtx/lzRU0sVmNsbd51co9xNJF0t6VtI8d98YJtv7hGX/WtI4M3vd3UtSxBe5srKy+HxpaWmEkQC178cff5QUHOd5eQxHgG1TVlYWP6ZKSjL6qx3IOYnnKInnLgDSJ+oEN9Y9+cEKrz+oIMEdphomuO7+lILksOLrX0m6xsy+D8u8UFJlCW5jBa2jA919U7j9Okl3m9kGSfdL6mdmP3P3txL28aakN5Pse4Wkf5hZiaTHwn2nSnDfknSau3u4/RpJl5vZ4QrqZZSk+939woR9rAxbdY9UcA3zAEnXVYij3PPwtU2SPpL0GzNrLuk4BfW+xbqZZPny5fH5Ll26RBgJkD5Lly5VYWFh1GEgyy1dulRvvPGGJKmoqCjiaICfruXLl6tdu3ZRhwHkvMi6KJvZ7pJ6KuiO/FCFxf+StE5SBzM7rJZ3PSV8PLSKkZqviyW3FYyV9GU4P3Ar972HmRWkWO/GWHJbwbSE+S26Ibt7maQXw6cH1DC2xPgOT7WSmQ2XNHUrygcAAACAtImyBfcMSSbpZXdflLjA3Veb2ZOSTlPQyvtaTQoOr939nYLrXttLaiapYjLbWFILSV8nKWKjpJnJynb3TWY2XUGX465J9t1U0jkKRoPeR0EX7PwkRbWVVFnf2i1agUNLw8cV7v5ZFesku0ZYZnagpLMVJLHFkrZX8HeoGFul3P1eM3tG0pJU66VTq1at4vOzZ89WQUGq3wuA7NK/f3ApfJs2WzMMAVBemzZt1K1bN0nSpEmTIo4G+GkpLS2N9zRLPHcBkD6RJLjhdZ9Dw6cVuyfHjFOQ4A4wsxHu/l01yz5U0r8VJJYx3ym4PtYVJLo7ha83UfIE92t3/zHFbmKJXesK+26voAU1MUH8XsEtkGKtwbEz1iaVFR52SU5mY/hY2fLEdbZIqs3sfEmjtbnl3iWtkhR7r40k7ZAqtkyReF1iQUEB3TiRUxo0aCBJXH+LWpGXlxc/pviuBKLDdzpQN6LqonyMNieB98duj5M4KRgISQpaGAdUp9DwFjoTFCS3cxTcS3cHd2/q7m3cvUBSt8RNauPNJBir4H0tUjCY1I7u3sTdW4f7Trz4qbb3nZKZ7aNggKx6Cq4DPlhSQ3dv4e4FYXx/iCI2AAAAAKgNUXVRPrPqVbZYf0w11jtU0q6SyiQd7+7JutBWpy/rTma2nbuvr2R5LFFdFnvBzNpJil0vfJq7v7GV+06XkxW0Xs9VwuBZFdDPFwAAAEDWqvMWXDNrpeA+rFKQdDVNMR0crneYme1djeJjQ9MtryS5laSjqlFOfQWjFW/BzEzBSMWS9HaSfUvSu9uw73SJxfdeJcmtFG18AAAAALBNouiiPFjB9aGrJE129+9STG9JmhduV51W31XhY5twoKlyzKytglv0VMcV4bXCFQ3R5mRxYpJ9S9KBSfbdVME9eKMSi2//MEkvx8z6KhjVGsBPWOumDeITqie/dev4BAAAohVFghtLVJ9K0QU40WPh4+nhNbapvCJprYJrSP8VDvokM8szs2MkTVcwsFJVvlcwyvD4MCmWmTUMb49zV0L8iaMdz5X0eTg/xsziN2cNB76arkpGNq4jsWuaO0q6w8xaSpKZNTGzsyX9n6RvogoOQGZ48/Kj4hOqp/Orr8UnAAAQrTpNcM2sm6R9w6ePpVo3QWy9NpKOS7Wiu6+S9Kfw6RGSPjazNQpGUX5Wwe2CzqjGPpdLukjB4FZfmNkKSasl3SOpoaT3VKFFOez2e56CUYw7SnrbzNaa2VoFtznaW9Kp1dh3Wrj7i5IeDZ+eK+kbM1upoGX3bgUJ+shoogMAAACAbVfXLbixpHCVpOeqs4G7f6Ag+UrcPtX6dytIhKcrSGzrK7itz20Kug5/UM393qFgtOdnFdziZ5OC7tL/K+lQd9+itdPdn1GQWE9RcGug+gpuQzRWUpcwyYzSryX9XtL7Cm4NlKegPi6T1F1BfQEAAABAVqrTUZTd/beSfrsV2+1b4flIpWhtdPd/K7gXbmWS3gbH3R+Q9EDC8+clPV/tQINtXpd0fIrlle17emVxVRZfJeuMVCV1E7Yyjw6nZKosHwAAAAAyVVS3CQK2SZs2bbRkyZL4PIDa8cLcpfH5o/bhs1UdK1/c3DmnRZ8+EUYCINNwvgLUPRJcZKW8vDwVFhZGHQaQc856cPPdzxaNSjnsAULzzzk7Pn/Igk8ijARApuF8Bah7UYyiDAAAAABArSPBBQAAAADkBBJcAAAAAEBOIMEFAAAAAOQEElwAAAAAQE4gwQUAAAAA5AQSXAAAAABATuA+uACQYWbMmCFJ6tmzZ93v/NCL47OR7L8G1qxZE58fPny4mjZtGkkcNybMZ2qdzZkzR506dYo6DAAA0o4WXAAAclynTp00aNCgqMMAACDtaMEFgAzj7pHt+/jbZsbnn5k+PbI4qmPt2rWaN2+eJKlDhw5q0qRJJHF8cOKv4vPTn3wqkhgAAEDAojyRQvYys0JJSyRpyZIlKiwsjDgiAAAAAJmmpKRERUVFsadF7l6Szv3RRRkAAAAAkBNIcAEAAAAAOYEEFwAAAACQExhkCgAQN/7Nz+Pzgw7eJcJIsseyRx+Nz7ceODDCSAAAAAkuACDu8ic+iM+T4FbPwiv/HJ8nwQUAIFp0UQYAAAAA5AQSXAAAAABATiDBBQAAAADkBBJcAAAAAEBOIMEFAAAAAOQEElwAAAAAQE4gwQUAAAAA5AQSXAAAAABATiDBBQAAAADkhPpRBwAAyBx9OrSOOoSs07xXr6hDAAAAIXP3qGNAFjKzQklLJGnJkiUqLCyMOCIAAAAAmaakpERFRUWxp0XuXpLO/dFFGQAAAACQE0hwAQAAAAA5gQQXAAAAAJATGGQKABB3ywvz4/MXHdU+wkiyx5f/GB2fb3vhiAgjAQAAJLgAgLjRLy6Iz5PgVs+S226Lz5PgAgAQLbooAwAAAAByAgkuAAAAACAnkOACAAAAAHICCS4AAAAAICeQ4AIAAAAAcgIJLgAAAAAgJ5DgAgAAAAByAgkuAAAAACAnkOACAAAAAHJC/agDAABkjtN+1i7qELJOq1NPjToEAAAQMnePOgZkITMrlLREkpYsWaLCwsKIIwIAAACQaUpKSlRUVBR7WuTuJencH12UAQAAAAA5gQQXAAAAAJATSHABAAAAADmBQaYAAHGXPf5+fH7USQdEGEn2+OzPV8Tnd7/u+ggjAQAAJLgAgLgJb30RnyfBrZ7lEyfG50lwAQCIFl2UAQAAAAA5gQQXAAAAAJATSHABAAAAADmBBBcAAAAAkBNIcAEAAAAAOYEEFwAAAACQE0hwAQAAAAA5gfvgYmvFfxwpLS2NMg4AtWjjmm/i8yUlJRFGkj2Wb9wYn6fOAAAor0KukPYGVnP3dO8DOcjMDpL0TtRxAAAAAMgand393XTugC7KAAAAAICcQAsutoqZ5UvaL3y6XNKmbShuqqS+2xzUTwf1VXPUWc1QXzVHndUM9VVz1FnNUF81R53VDPVVffUktZL0sKRO7r4hnTvjGlxslfDArJXuBWa2wd25cK2aqK+ao85qhvqqOeqsZqivmqPOaob6qjnqrGaorxr70szWpTu5leiiDAAAAADIESS4yAT3Rh1AlqG+ao46qxnqq+aos5qhvmqOOqsZ6qvmqLOaob5qrk7qjGtwAQAAAAA5gRZcAAAAAEBOIMEFAAAAAOQEElwAAAAAQE4gwcU2M7OmZjbSzD4ws+/MbJWZvWVmfzSz7bax7DZm9jcz+9jM1pnZCjObaWZnmZnV1nuoa+moMzNrbma/MrNrzOwZM/vKzDychtbyW6hTaaqvIjP7nZk9ZmafhMfXOjNbaGYTzKx3bb+PupSmOjvSzK43s2lmtsDMVprZBjNbZmb/MbMLzaxRbb+XupDO77Ek+7o74bO5qDbLrktpOsZGJtRNqmnP2n4/6ZbuY8zMCszsWjObHf6vXGdmi83sWTO7NLx/fVap7Tozs+JqHl+xaWw63le6pPMYM7OTzWyymZWY2XozW2vBudl9Ztaptt5DXUtznZ0Q1llpWGdfmdlTZpZ19841s8Zm1tfM/mxmj4ffLbHPycha2kftnfO7OxPTVk+SdpW0UJKH01pJPyQ8f0dSi60su4ukrxPKWiNpQ8LzZyVtF3UdZEqdSRqaUEbFaWjU7zuT6ktSO0mbKtTRWknfV3jtn5Lyoq6DTKizsNxnKtTPd+GU+NpnktpHXQeZUF+V7KtXhWNvUdTvP5PqTNLIcPv1kkpTTMVR10Em1FdC+adKWpVQ3roKz11S86jrIeo6C7/7Ux1XpZK+TdjH76Kuh6iPMUkNJD1d4VhaI+nHhOdlki6Kug4yqM7yJD2cUM4mSSskbUx47R9Rv/8avqeeFY6BxGlkLZRfq+f8kVcYU/ZOkupLej888EokHRW+Xi/8Z7s6XDZlK8puJumrcPu5krqGr28n6TwFJz8u6c6o6yGD6mxoWGf/lnSdpH4JXwxDo37vmVRfkorD7V6QdLqkwoRy95X0ZELdXRt1PWRCnYVl/F7SBZIOktQ04fUdw9djPxB8JKle1HURdX0l2VdjSZ+E319vKUsT3DQfYyPDbadH/T6zob7Cck5RkGC4pHsk7ZuwrKmkHpL+LqlJ1HWRKXVWxb5vC8v+Xlnyo0CaP5NXJ/w/vENSUULZXSTN1OYkrkvUdZEhdTYqoc5ulbRj+HoTSX/U5sTtwqjroQbvqaeCJP0FSTdJGqjN5+kjt7HsWj/nj7zCmLJ3knRmwgf40CTLT0tY3qeGZV+b8A9mtyTLLwuXb1QWtRaluc62aGlMKGto1O89k+or/DLtnGK5SZqqzb8iNoy6LqKus2rue3hC2d2jrotMqy9Jt4TlXCfpAWVvgpvO77GRyr0EN531tbOCk06X9Ieo32s21FkV+22YUJ8PRV0PmVBf2tzCOb2S5c3C/5MuaVTUdRF1nUnaSZtbgZ+oZJ0bwuUrJe0QdV1U830lO8dcpNpJcGv9nJ9rcLEthoSP/3H315Msf1TBF6MUtJLVRGz9R919YZLltynoGpkn6dc1LDtKaaszdy/blsAyVFrqy91Xufs7KZa7pDHh0+0l7VPdsjNAOj+XVXkjYb5tLZedLnVSX2bWTdKFkuYrSHCzWZTHWDZKZ31dKKmFpHcV/ICSK6I6xk5SUJ+SdH8tlptu6ayvncPHt5MtdPdVCr7XpOD/ZbZIV531UdCtW5JurmSdm8LH5pJOrEHZkUnzOWatn/OT4GKrmFljSd3Dp1OTrRMmCc+GT4+uQdl7S9qlirK/U9AtpkZlRymddZaLMqC+fkiYz6vlstMiA+qsR8L8p7Vcdq2rq/oyswYKfjAxScPd/YcqNslYGXCMZZU6qK/YieHDYTlZL+Jj7MzwcYG7z6jFctOmDurrs/CxSyX7byapffg0aRKcadJcZ7smzP+3krJXSFq2FWXnnHSd85PgYmvto83Hz4cp1ostKzCzltUse78k26cqe99qlhu1dNZZLoq6vnqGj+u1+dfpTFfndWZmjcxsLzO7XNLfwpdfdvdsONGpq/r633Bf/8yWk+YU6qrOOprZh2b2fTiyaWy01oO2oqwopa2+zGw3SYXh09lmtr+ZjQ9Hav3RzL40s4lm1j1VORkoku9+M9tdwSBwUjDAYLZId33dFT72NLM7zKxIkizQWcHgg9tLel3BwErZoK6OsVQ/jseW7b8V5eaStJzzk+BiaxUmzC9JsV7issJK19q2sncws2zoFpPOOstFkdVXeOJ4Tvh0oruvro1y60Cd1JkFtyNxM4tdMzNf0vUKumVNVjDAWTZIe32FCdklkpZKurgm22aouvpc7qTgJHSdguOqvaSzFCRy2dTFO5311T5hvruC1rPTFFwT+YOkIkkDJM00syurWWYmiOq7f5iCXhYbJY2rhfLqSrrr6w4FXWo3SfqdpC/NbI2CY2y2pD0VXFPaJ4sulUpnnS1KmN8v2QpmVqBgcMaalJur0nLOT4KLrdU0Yf77FOslLmta6Vp1V3aUcvV9pUsk9WXBfVwfUzDi7deSLt3WMutQXdVZmYKEbanKd+V+TNIlYferbJDW+jKz+gq6JtdXMFrmtzULLyOl+xhboOAHgb0VDO62o4KRR49RcDJtkq4wsz/WoMwopbO+WiTMX6tgJNifS9re3ZtJ6ihpuoI6u8bMTqpmuVGr8+9+M8tTcCcCKRg1t3Rbyqtjaa0vd9+kYJCfYQqug5SCFtvYPWIbKvhRpUl1y8wA6ayzlxTcQkmSrqhkncTXd6hmubkqLX8LElwACIUJyXgF1xptkPRrdy+JNqrM4+7L3b3A3QsU/BDQTkEL7i8lvW9mwyMNMHNcKqmTpGfc/V9RB5MN3P0Rd7/Z3ee7+4bwtfXu/pykwxXcXkmSRobX/v2UJZ7DmaT+7v5CmJDI3f+r4DMZS9auquP4ssmxClq8pewaXCrtzGwnSS8qGPn9dQWfw+YKBp86SdJySedKmhXrvvxT5u5fS/pH+PTnZvawmXUws3wz28XMblBw65sN4TqbIgk0x5HgYmutSZhvnGK9xGVrKl2r7sqOUq6+r3Sp0/oKf8F/RMGIhhslDQpPqrNJnR9jHvjS3f+sYHTDfEl3mdmB21JuHUlbfZnZvpKuVNDi8buah5axIvseCwfnujx8ur2C0UozXV39r3wx2cjw4eAsd4RPDzCzNtUsO0pRHGNnhY9LVMlANxks3fU1TsGYFDMkHePur4Z3Iih19ycUJLxfS9pdQVflbJDuOrtcwSjMUvB/ca6C8TwWS/ofSbO0+TrvlTUoNxel5W9BgoutldiqleoXu8Rl1W0Jq2nZq8N/4pkunXWWi+qsvsLk9mEF16uVSfqNu//f1pQVsUiPMXd/XNLnCv63nFnF6pkgnfV1h4IufNdLWmlm2ydOCrotS8FYLbHX86sdeXSi/h5LvJ3H7rVYbrqks74Sr1ebm2K9xJFcd610rcxRp8dYmPQfHz59IIuuI41JW32Z2T6SfhE+/VuykbrdfZmkB8OnJ5mZVafsiKX1GHP3je5+mqTjJE2UNE9BcjtTwa29jtDmhC1bBrFMl7Sc85PgYmvN1eZuFUkvoq+wrLQG1+UljqJWnbKTDsOegdJZZ7moTuoroeV2oDYntxNrWk6GyIRjLHbSvWctl5sO6ayv3cLHUQp+ba44xe7lt0vCa+dVs+woZcIxlk3SWV//VfCdVZXEhCMbbiVU18fY6Qp+cEq8/3k2SWd9JY5Ym+rWbwvCx8aSWlez7CjVyTHm7v9294Huvo+7F7v7Ee5+W3j5RddwtddqWm6OScs5Pwkutoq7fy/p1fDpscnWCX/FOyZ8WpOunvMVtAKlKruJNt9zMyu6kaa5znJOXdRXmNyOl3SqNie3j6beKnNFfYyFZccSu4zvXh91fWWjDKizbgnzC2u57FqXzvoKu2y/HD7dJ8WqsSTFVX6E14wUwTEW623yH3f/LOWaGSjN9ZV4fWiq1v/Eru8Z36Mu6u+xcHT92OfywVTr/gSk5ZyfBBfbIjaMfi8zOyTJ8lO0uQtZtT/AYReY2PoDzaw4yWrnKbgGq0xB61u2SEud5bC01VdCy+0ABdfc/jqbk9sEaamzcACuqpwhqSCcn17dsiOWru+xYne3yqaE/S5OeP3WrX8bdSpdx1jKro1m1kBBl29JWqtg4JtskM7v/bHhY5/wnqTlhN3hY9eAz3L35TUsPyp18r/SzA5XMGK3lN2DS6WrvhKv6z432Qph8nF6+PR9d19bg/KjFMn5mJk11uZ7C/+fu8+rrbKzUdrO+d2diWmrJgVdet5X8KvwlwrugSYFP5ycImlVuOzfSbYdGS5zScVJljeT9FW4/CNJXcLXt1PwJftjuOzOqOshU+osXGenClNs/fMrvN446rqIsr4U3GB9Qrhsg6RTon6vWVBnPRW0Fg2W1LbCsr0UDC6yIdz2E0mNoq6LKOurGvt9INxuUdR1kCl1JulISS9UPMYUDFzWR9KbCdteEnU9RF1fCWXMCpcvDOupXrhsHwW3LHEFJ4a9o66LTKizCuvGPoffSGoQ9fvOxPqS9HTC8ock7aGg23u+pMMUjGweW3561HWRIXV2iIKBpvaVtF342nYKWijfCbf7XFLrqOuhhnXWQuXPJT8P38tNFV7fvob1Vevn/JFXFlN2T5KKw3+qsQN3raR1Cc/fkdQiyXZV/gNScKuWrxPWW61gFLrY82nZ+A8pzXXm1ZxGRl0PUdaXggEeYsvWK7iNRqrp1KjrIQPqrGeFY2idgttDtK89FAAADKRJREFUfF/h9TmVHZ+ZOqXzM5linw8oSxPcOjzGvg+PscTv/TJJ10f9/jOhvhLWKVBwUphY9rcVvuN+G3UdZFKdhevtEJbpkkZH/X4ztb4UJCxvV/hsrtXmHzRj001R10EG1dmJCcs3KfgBZWPCax+kOjYzdVJwiUN1zjEfqEl9hevU6jk/XZSxTdx9kaQDJF2j4EJxV/ClN1vSnyR1c/etGgLd3WcruFH9LQoGMMhX8OXziqTfSurr7j9WXkJmSmed5aI01Vfid1++guuHUk2Ntv4d1L001dlsBS1r/5T0noJft5sr+Of9qaTHFAzU1SXcf9bgM1lzaaqzD8JtJym4LmudgmNsnYJj7nZJndz9ilp4C3Uqzf8rSyV1Dst5Kyy3kYKT0TGSOrv7fdv2DupeHXwuB2rzSLbZ3D1ZUvrqy4P7unZTcCulaZKWKvi/uVHSZwruQNDD3S/Z9ndRt9J4jM2WdLOC3hXLJDVVkOS+IGm4pIOy7f9kutX2Ob+FWTMAAAAAAFmNFlwAAAAAQE4gwQUAAAAA5AQSXAAAAABATiDBBQAAAADkBBJcAAAAAEBOIMEFAAAAAOQEElwAAAAAQE4gwQUAAAAA5AQSXAAAMpyZeTiN3IYyihPKGVp70UWjNuqkivIfCMtflI7yAQDpUT/qAAAAyGRm1ljSIEknSjpQ0k6S8iStlvS5pI8kzZL0nLvPjypOAABAggsAQKXM7BBJj0oqTrJ4x3A6SNJvwvUbufsPdRZgjglbS3eVNM7dh0YbTWrZFCsA/JSQ4AIAkISZ7SXpOUk7hC9NkfSYpI8l/SCppaQDJPWS9HNJjSIIs9rcfZEkizqO2uLuaX0vYdI6NJ37AADUPhJcAACSu16bk9uz3P2fSdZ5SdKtZraDgmSorI5iAwAASZDgAgBQgZnlSTo+fPp2JcltnLuvlvSP/2/vTmPtqsowjv+fIrQprZEZikBDIRSQQQqIDEVRURspqUWQsVRA1KASZ1BCa5SoAZEgJFiCxQGEQgEnCGhpJYhSFJDRDpYZLUNbLR3o8PphrePZPd33TPeeXnPu80tu9l57r73Oe24/NO9da7+r44GZmZlZXa6ibGZmtrHtqC45XtjuIJKeyZV4pzfoN6VSFbjJcY+RdJukFyWtkvSspGmSRtV5pukqypKOlHSdpAWS3pC0XNJTkq6s9xk1Y4yWdLmkRyS9LmmNpFckzZF0saTdC31n5+++W740qRBr5Wd2zfilVZQlLczX/9JEjEMkLcv9Z9bcK62i3Eqskr6f2+sk7dxEPL/J/V+VtEWj/mZmtjEnuGZmZhtbXTjfu9+iKCHpIuB3pKrOI4DBwK7A2cBjksb3YuzBkq4H7gMmA6OAocCWwGjgPOApSZ+oM8YgSZcAjwPnkypPb0VaNbYtMBaYAlzXbpwN/DwfD5I0ukHf46guQ/9ZB2K5Nh8H0eB9XkkjgA/m5k8j4s0OxGNm1vWc4JqZmdWIiCXAM7m5v6QLJf0//J85DvgmaVb5HOAQUpGry4E1pFnnGZIOaHP8m4Ez8vndpKRsLHAo8CngaWBz4FpJHykbAPghcAFpK6XFwMXA+4CD8vHLwB+B4mz1ZGA/4KXcviO3iz+Tm/wOxUT11AZ9T8vHpaQiYs1oOtaIeBK4P/c7s8G4k0i/M4C6S+LNzKxnfgfXzMys3BWkxBFSwalzJf2SlJzNBRZGRFNLivvQIcCjwNj83m/FbEl3k5K0LYCrgSNaGVjSWcB4UqGsEyLi9poucyX9BLgTOBq4UtJdEbG2MMY44NO5+RDwoYh4rWacWcClknapXIiIRfn5NfnS0oh4vJX4C2PNkzSX9Ls6BbiorJ+krYEP5+aMiFhd1q9k/FZjnUb6t9hD0tERMaeHfpUEfm67393MzDyDa2Zm1pMrgB8V2ruSlujeAMwHXpF0q6QTJW3KPxifU5PcAhARdwHX5+bhkt7Z7ICSBHwtN68pSW4rn7ES+ExujiTNHhddmI+rSUlybXJbHOv5ZuNrQ2UWd3dJ7+6hz4mk2WioLmvuhBnAsnxeurRb0lHAnrnp2Vszs15wgmtmZlYiknNJy2p/TVoCXLQN8FHgJtK7r00nlL3weETMrXO/+F7rB1oYdx9gj3w+o17HvOy2krj+L3nMM6KH5+bMiHi2hc/va78AKjPLp/XQp7J8+TngD50KJCJWkP4oAnBC3lKqViXxXQHc2KlYzMwGAie4ZmZmdUTErIg4DtgaOBb4OjCTapIHqQDTHEn7djicBxvcfwhYn8/3b2Hcgwvn95ZUBd7gh5TcA+xYeO5AQPn8vhY+u89FxGLgntzcaIZd0kiqS7hv2ARLzafl41Dg4zWxDAM+lpu3lM3Om5lZ85zgmpmZNSEilkfEPRFxSURMJCV3E4EXcpfhwA86HMbiBjGuAioJ0jb1+tbYvs14hhbOtyucv9zmeH2pskx5W6rViStOoZqMd6J68gYi4mGgsm1R7TLlk0hVqqFzlaXNzAYMF5kyMzNrQy6uNFPSfNLM6RbAMZK2jojXO/WxHRp3s8L5RGBek88t6UAsfeV2YDkwjLQcuVglubI8+dGIeGITxXMtMAZ4l6R98lJvqCa8C+jgUmkzs4HCCa6ZmVkvRMRjkv4MHEVaGTUKqCS4leXCjVZMbdngfsUO9W5KGkJ1X9ceCzyVeLVw/u82q/gWx9ipjef7VESskHQbcDpwvKRhEbE8vyu9T+7W8dnbghuAy0iz3mcBX5S0F9X3lq/rh6rcZmZdx0uUzczMeu+lwnkxSflPPm7V4PnRTX7OoQ3uj6H6f/tjTY4J8HDh/MgWnqsdo/Ldx7Y5Rl8neJUEdigwIZ9Xik6tp1r8qR0txZrfrb2pEoOkzanO3q6jWgHbzMx6wQmumZlZL+QtdsbkZgDPFG7/Ix/H5H5lz28PvL/Jj3uHpDF17hff77ynx14bexiobNtzdi581JK8LPv+3JwgabdWxwBW5ePgNp4t83uq7wOfKmkQ1SJP90bES+WPNaWdWCvFprYHjifNLgPc1ctYzMwsc4JrZmZWQ9IwSQ9KGi9pswbdp1LdYue+iCgu1Z2TjztRTWaKnzMYmA4MaSG8aWUJqKRjgTNz808R8ddmB4yI9cC3c3Nn4EZJQ3vqL2mIpPPykuii7+TjYOCWvHVQT2PsUnK5koyOai7y+iJiHWnLIEh/RDgZGJHbvd37tuVYI+IBoPLO75VUl3J771szsz4iv+5hZma2oZxAVpYXvwzcATwALCJVKR5O2obnNKp7wa4GjoyIhwrjbAvMB96W738XuJO0JPUA4HPAvqTtfw4DiIiNZnrz1jyQilkdnMf8LvAo6f3d8cBngc2BN4HDcuXe4hgjc/wAkyNies19ATcDJ+RLzwHX5O+9hFSsaU/Su8YT8ncaHhHLa8a5Bvhkbi4GriJtG7SEtFT7QNL+wWsj4r01z36LtA0TwAX5d/VGbq+MiBdLfidTI2IKPZB0ENUKxktz3CuBHettySNpOjAJeDYiRpbcbzrWmufOBy4vXFoMvD0iavdZNjOzNjjBNTMzq5FnJhex4T6v9bwATIqIWSVjTSAljmWFHdcC55O22LkYGia4U0nLoKf0EMcq4OSIuL1kjJHUSXBzn7eQCiGdR+NVXm8A20XEypoxBgGXkr5X6bLsbE5EvKfm2Z2Bv5H2HK7bv9kEN/d9Eti7cOnmiDipwTPTqZ/gNh1rzXPbAC9SXdp8WUR8qV4sZmbWPC9RNjMzq5H3kx1BqnB7EWmLmQWkpG4daXZ3PnArMBnYqyy5zWPdRpqdnQH8C1hDKkp1E3BERFzVYmxTgWOBXwH/JM3YPk9a5rp/WXLbwthrI+LzwH6kPX0fIc28riPNXD9BKtx0BrBTbXKbx1gfEV8gzdReDTxF+n2tBV4BZgPfoGTJdp71PDR/lwVU33Ptrdpqyb2untxurBHxGvDbwiUvTzYz60OewTUzMxsAJO0OLMzN0yNiU26RYwWS5pGWez8QEYc36m9mZs3zDK6ZmdnA8NbC+bJ+i2KAkzSWlNyCZ2/NzPqcE1wzM7OB4cDC+bx+i8K+mo9LgRv7MxAzs25UVvDCzMzMuoCkLYG9SJWaL8mXF0XE3/svqoFF0nBgB9IM+unAuHzriohY0W+BmZl1KSe4ZmZm3esQ4N5CO4Cv9FMsA9VE4Mc1154GvtcPsZiZdT0vUTYzM+t+y4BZwLiIuKW/gxmg1lPdW/hoz96amXWGqyibmZmZmZlZV/AMrpmZmZmZmXUFJ7hmZmZmZmbWFZzgmpmZmZmZWVdwgmtmZmZmZmZdwQmumZmZmZmZdYX/AjlArFO5lgMWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1008x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 4))\n",
    "\n",
    "plt.boxplot(boxplot,vert=False,widths = 0.6, boxprops=dict(linestyle='-', linewidth=1.5),\n",
    "             flierprops=dict(linestyle='-', linewidth=2.2),\n",
    "             medianprops=dict(linestyle='-', linewidth=2.4, color = \"k\", ),\n",
    "             whiskerprops=dict(linestyle='-', linewidth=2.2),\n",
    "             capprops=dict(linestyle='-', linewidth=2.2),\n",
    "             showfliers=False,)\n",
    "\n",
    "plt.axvline(x=0.3, color='#1f78b4', ls='--', lw=3,label='Objective')\n",
    "plt.axvline(x=0.4, color='#c82423', ls='--', lw=3,label='Subjective')\n",
    "plt.legend(loc=(0.32,-0.5), edgecolor='k', ncol=4)\n",
    "# 获取当前的 Axes 对象并调整边框\n",
    "ax = plt.gca()\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_linewidth(2.2)\n",
    "\n",
    "plt.yticks(fontsize=25)\n",
    "plt.yticks(np.arange(1,3,1),['Alabama', '  Arkansas'],fontsize=25)\n",
    "plt.xticks(np.arange(0,1.1,0.1),fontsize=25)\n",
    "plt.xlabel('Subjectivity',fontsize=28)\n",
    "\n",
    "# 自定义图例，使用白色框和带斜线的白色框\n",
    "legend_elements = [\n",
    "   # Patch(facecolor='white', edgecolor='black', label='Alabama'),\n",
    "    #Patch(facecolor='white', edgecolor='black', hatch='//', label='Arkansas'),\n",
    "  Line2D([0], [0], color='#1f78b4', label='Objective',ls='--',linewidth=3,),\n",
    "    Line2D([0], [0], color='#c82423', label='Subjective',ls='--',linewidth=3,),\n",
    "]\n",
    "plt.legend(handles=legend_elements, frameon=True, edgecolor='black',loc=(0.52,0.8),ncol=4,fontsize=20,labelspacing=0.,\n",
    ")\n",
    "#plt.xlim(-0.1,1.1)\n",
    "plt.ylim(0.,3.1)\n",
    "\n",
    "# 显示图像\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c900928-43fa-4204-90c5-9164dddff21c",
   "metadata": {},
   "source": [
    "# Fig 2 b& c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "57becbdf-d815-4e6a-8d01-962a4ee09c64",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('./AL_lexicon_250210.csv')\n",
    "data = data.drop(['Unnamed: 0'],axis=1)\n",
    "other_emotions = [ 'trust', 'anticipation', 'joy', 'surprise']\n",
    "data['other_emotions'] = data[other_emotions].mean(axis=1)\n",
    "data['emotion'] = data[['sadness','fear','disgust','anger','other_emotions']].idxmax(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3df7842b-92b0-409c-ae47-da3644dbc45e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "979f3c5f-2dcc-4f70-aa01-593ecc0a5480",
   "metadata": {},
   "outputs": [],
   "source": [
    "data2 = pd.read_csv('AR_lexicon_250210.csv')\n",
    "data2 = data2.drop(['Unnamed: 0'],axis=1)\n",
    "other_emotions = [ 'trust', 'anticipation', 'joy', 'surprise']\n",
    "data2['other_emotions'] = data2[other_emotions].mean(axis=1)\n",
    "data2['emotion'] = data2[['sadness','fear','disgust','anger','other_emotions']].idxmax(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "46f69d53-6e04-44d7-b593-a409d37f1ad2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data3 = pd.read_csv('AL_jhartmann_new_250210.csv')\n",
    "data3 = data3.drop(['Unnamed: 0'],axis=1)\n",
    "other_emotions2 = [ 'neutral', 'joy', 'surprise']\n",
    "data3['other_emotions'] = data3[other_emotions2].mean(axis=1)\n",
    "data3['emotion'] = data3[['sadness','fear','disgust','anger','other_emotions']].idxmax(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "5e95b1c4-904f-4f57-b4b6-1c9c0e013f2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "data4 = pd.read_csv('AR_jhartmann_new_250210.csv')\n",
    "data4 = data4.drop(['Unnamed: 0'],axis=1)\n",
    "other_emotions2 = [ 'neutral', 'joy', 'surprise']\n",
    "data4['other_emotions'] = data4[other_emotions2].mean(axis=1)\n",
    "data4['emotion'] = data4[['sadness','fear','disgust','anger','other_emotions']].idxmax(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "7ee9ea2e-ea0a-49e2-aded-c936c808b0dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "from matplotlib.font_manager import FontProperties\n",
    "# 定义字体\n",
    "ttf_path = '/Users/liuanqi/Library/Fonts (Removed)/06-17-2024 19_25_42 GMT+9/Pretendard-Regular.ttf'\n",
    "custom_font = FontProperties(fname=ttf_path, size=30)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "82652ae8-6add-4300-9e4c-b2672f4d6122",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-84-5ac2c5417c44>:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  sub['emotion'] = sub['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
      "<ipython-input-84-5ac2c5417c44>:11: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  obj['emotion'] = obj['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
      "<ipython-input-84-5ac2c5417c44>:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  sub1['emotion'] = sub1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
      "<ipython-input-84-5ac2c5417c44>:13: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  obj1['emotion'] = obj1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "emotion_order = ['other_emotions','sadness','fear','disgust','anger']\n",
    "\n",
    "sub = data[data['Subjectivity'] >=0.4]\n",
    "obj = data2[data2['Subjectivity'] <=0.3]\n",
    "\n",
    "sub1 = data3[data3['Subjectivity'] >=0.4]\n",
    "obj1 = data3[data3['Subjectivity'] <=0.3]\n",
    "\n",
    "# 将不在指定顺序中的情绪替换为'other_emotions'\n",
    "sub['emotion'] = sub['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "obj['emotion'] = obj['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "sub1['emotion'] = sub1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "obj1['emotion'] = obj1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "\n",
    "# 统计每种情绪的出现次数\n",
    "emotion_counts1 = obj['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts1.columns = ['emotion', 'count']\n",
    "emotion_counts1['percentage'] = (emotion_counts1['count'] / emotion_counts1['count'].sum()) * 100\n",
    "\n",
    "emotion_counts2 = sub['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts2.columns = ['emotion', 'count']\n",
    "emotion_counts2['percentage'] = (emotion_counts2['count'] / emotion_counts2['count'].sum()) * 100\n",
    "\n",
    "# 统计每种情绪的出现次数\n",
    "emotion_counts3 = obj1['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts3.columns = ['emotion', 'count']\n",
    "emotion_counts3['percentage'] = (emotion_counts3['count'] / emotion_counts3['count'].sum()) * 100\n",
    "\n",
    "emotion_counts4 = sub1['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts4.columns = ['emotion', 'count']\n",
    "emotion_counts4['percentage'] = (emotion_counts4['count'] / emotion_counts4['count'].sum()) * 100\n",
    "\n",
    "# 定义柱的宽度\n",
    "bar_width = 0.3\n",
    "index = np.arange(len(emotion_order))\n",
    "\n",
    "fig, axes = plt.subplots(figsize=(12,14), ncols=2,sharey=True)\n",
    "fig.tight_layout()\n",
    "\n",
    "bars1 = axes[0].barh(index + 0.15, emotion_counts1['percentage'], bar_width, color='#2878b5', edgecolor='black', linewidth=1.5, label='Objective', alpha=0.99)\n",
    "bars2 = axes[0].barh(index - 0.15, emotion_counts2['percentage'], bar_width, color='#c82423', edgecolor='black', linewidth=1.5, alpha=0.99, label='Subjective')\n",
    "\n",
    "bars3 = axes[1].barh(index + 0.15, emotion_counts3['percentage'], bar_width, color='#2878b5', edgecolor='black', linewidth=1.5, label='', alpha=0.99, hatch='') \n",
    "#plt.bar(index + 0.15, emotion_counts3['percentage'], bar_width, color='none', edgecolor='k', linewidth=1.5, label='NRC Lexicon', alpha=0.99) # 描边框\n",
    "bars4 = axes[1].barh(index - 0.15, emotion_counts4['percentage'], bar_width, color='#c82423', edgecolor='black', linewidth=1.5, alpha=0.99, label='', hatch='')\n",
    "#plt.bar(index + 0.15, emotion_counts4['percentage'], bar_width, color='none', edgecolor='k', linewidth=1.5, alpha=0.99, label='Transformers', bottom = emotion_counts3['percentage'])\n",
    "\n",
    "# 设置标签和字体属性\n",
    "# for bars in [bars1, bars2]:\n",
    "#     for bar in bars:\n",
    "#         # 增加 bar.get_height() 的值，使文本显示在更高的位置\n",
    "#         axes[0].text( bar.get_width() +8.5,  bar.get_y()+0.06, f'{bar.get_width():.1f}%', \n",
    "#                  ha='center', va='bottom', fontsize=25, fontweight='normal', color='black')\n",
    "# for bars in [bars3, bars4]:\n",
    "#     for bar in bars:\n",
    "#         # 增加 bar.get_height() 的值，使文本显示在更高的位置\n",
    "#         axes[1].text( bar.get_width() +7,  bar.get_y()+0.06, f'{bar.get_width():.1f}%', \n",
    "#                  ha='center', va='bottom', fontsize=25, fontweight='normal', color='black')\n",
    "axes[0].invert_xaxis() \n",
    "axes[0].grid(ls=':', lw=1.6, color='grey')\n",
    "axes[1].grid(ls=':', lw=1.6, color='grey')\n",
    "#axes[0].set_yticks(index + bar_width / 2,['Others','Sadness','Fear','Disgust','Anger'] ,fontproperties=custom_font, fontsize=35, fontweight='normal')\n",
    "axes[0].set_yticks(index  )\n",
    "axes[0].set_yticklabels(['Others','Sadness','Fear','Disgust','Anger'],fontproperties=custom_font, fontsize=35, )\n",
    "axes[0].set_title('Lexicon-based', fontsize=40, pad=12)\n",
    "axes[1].set_title('ML-based', fontsize=40, pad=12)\n",
    "axes[0].set_xticks(np.arange(0,60,10))\n",
    "axes[0].set_xticklabels(['0','10','20','30','40','50','60'], fontproperties=custom_font,fontsize=30)\n",
    "axes[1].set_xticks(np.arange(0,60,10))\n",
    "axes[1].set_xticklabels(['0','10','20','30','40','50','60'],fontweight='normal',fontproperties=custom_font,fontsize=30)\n",
    "\n",
    "for spine in axes[0].spines.values():\n",
    "    spine.set_linewidth(2.5)\n",
    "for spine in axes[1].spines.values():\n",
    "    spine.set_linewidth(2.5)\n",
    "\n",
    "# 自定义图例，使用白色框和带斜线的白色框\n",
    "legend_elements = [\n",
    "    Patch(facecolor='#2878b5', edgecolor='black', label='Objective'),\n",
    "    Patch(facecolor='#c82423', edgecolor='black', hatch='', label='Subjective'),\n",
    "   # Patch(facecolor='white', edgecolor='black', hatch='', label='Lexicon-based'),\n",
    "#    Patch(facecolor='white', edgecolor='black', hatch='/', label='ML-based')\n",
    "]\n",
    "legend = plt.legend(handles=legend_elements, frameon=True, edgecolor='black',loc=(-0.75,-0.17),ncol=2,prop=custom_font,fontsize=30,)\n",
    "legend.get_frame().set_linewidth(2.5)\n",
    "axes[0].set_xlabel('Percentage [%]', fontsize=30)\n",
    "axes[1].set_xlabel('Percentage [%]', fontsize=30)\n",
    "\n",
    "axes[1].set_xlim(0,50)\n",
    "plt.subplots_adjust(wspace=0, top=0.85, bottom=0.1, left=0.18, right=0.95)\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32cc1a86-059d-43a9-8351-fa75c9f53b2e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "de6ebf58-9734-462b-a8d9-563bbb659620",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-85-c58bfd590ad6>:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  sub['emotion'] = sub['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
      "<ipython-input-85-c58bfd590ad6>:11: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  obj['emotion'] = obj['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
      "<ipython-input-85-c58bfd590ad6>:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  sub1['emotion'] = sub1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
      "<ipython-input-85-c58bfd590ad6>:13: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  obj1['emotion'] = obj1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "emotion_order = ['other_emotions','sadness','fear','disgust','anger']\n",
    "\n",
    "sub = data2[data2['Subjectivity'] >=0.4]\n",
    "obj = data2[data2['Subjectivity'] <=0.3]\n",
    "\n",
    "sub1 = data4[data4['Subjectivity'] >=0.4]\n",
    "obj1 = data4[data4['Subjectivity'] <=0.3]\n",
    "\n",
    "# 将不在指定顺序中的情绪替换为'other_emotions'\n",
    "sub['emotion'] = sub['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "obj['emotion'] = obj['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "sub1['emotion'] = sub1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "obj1['emotion'] = obj1['emotion'].apply(lambda x: x if x in emotion_order else 'other_emotions')\n",
    "\n",
    "# 统计每种情绪的出现次数\n",
    "emotion_counts1 = obj['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts1.columns = ['emotion', 'count']\n",
    "emotion_counts1['percentage'] = (emotion_counts1['count'] / emotion_counts1['count'].sum()) * 100\n",
    "\n",
    "emotion_counts2 = sub['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts2.columns = ['emotion', 'count']\n",
    "emotion_counts2['percentage'] = (emotion_counts2['count'] / emotion_counts2['count'].sum()) * 100\n",
    "\n",
    "# 统计每种情绪的出现次数\n",
    "emotion_counts3 = obj1['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts3.columns = ['emotion', 'count']\n",
    "emotion_counts3['percentage'] = (emotion_counts3['count'] / emotion_counts3['count'].sum()) * 100\n",
    "\n",
    "emotion_counts4 = sub1['emotion'].value_counts().reindex(emotion_order, fill_value=0).reset_index()\n",
    "emotion_counts4.columns = ['emotion', 'count']\n",
    "emotion_counts4['percentage'] = (emotion_counts4['count'] / emotion_counts4['count'].sum()) * 100\n",
    "\n",
    "# 定义柱的宽度\n",
    "bar_width = 0.3\n",
    "index = np.arange(len(emotion_order))\n",
    "\n",
    "fig, axes = plt.subplots(figsize=(12,14), ncols=2,sharey=True)\n",
    "fig.tight_layout()\n",
    "\n",
    "bars1 = axes[0].barh(index + 0.15, emotion_counts1['percentage'], bar_width, color='#2878b5', edgecolor='black', linewidth=1.5, label='Objective', alpha=0.99)\n",
    "bars2 = axes[0].barh(index - 0.15, emotion_counts2['percentage'], bar_width, color='#c82423', edgecolor='black', linewidth=1.5, alpha=0.99, label='Subjective')\n",
    "\n",
    "bars3 = axes[1].barh(index + 0.15, emotion_counts3['percentage'], bar_width, color='#2878b5', edgecolor='black', linewidth=1.5, label='', alpha=0.99, hatch='') \n",
    "#plt.bar(index + 0.15, emotion_counts3['percentage'], bar_width, color='none', edgecolor='k', linewidth=1.5, label='NRC Lexicon', alpha=0.99) # 描边框\n",
    "bars4 = axes[1].barh(index - 0.15, emotion_counts4['percentage'], bar_width, color='#c82423', edgecolor='black', linewidth=1.5, alpha=0.99, label='', hatch='')\n",
    "#plt.bar(index + 0.15, emotion_counts4['percentage'], bar_width, color='none', edgecolor='k', linewidth=1.5, alpha=0.99, label='Transformers', bottom = emotion_counts3['percentage'])\n",
    "\n",
    "# 设置标签和字体属性\n",
    "# for bars in [bars1, bars2]:\n",
    "#     for bar in bars:\n",
    "#         # 增加 bar.get_height() 的值，使文本显示在更高的位置\n",
    "#         axes[0].text( bar.get_width() +8.5,  bar.get_y()+0.06, f'{bar.get_width():.1f}%', \n",
    "#                  ha='center', va='bottom', fontsize=25, fontweight='normal', color='black')\n",
    "# for bars in [bars3, bars4]:\n",
    "#     for bar in bars:\n",
    "#         # 增加 bar.get_height() 的值，使文本显示在更高的位置\n",
    "#         axes[1].text( bar.get_width() +7,  bar.get_y()+0.06, f'{bar.get_width():.1f}%', \n",
    "#                  ha='center', va='bottom', fontsize=25, fontweight='normal', color='black')\n",
    "axes[0].invert_xaxis() \n",
    "axes[0].grid(ls=':', lw=1.6, color='grey')\n",
    "axes[1].grid(ls=':', lw=1.6, color='grey')\n",
    "#axes[0].set_yticks(index + bar_width / 2,['Others','Sadness','Fear','Disgust','Anger'] ,fontproperties=custom_font, fontsize=35, fontweight='normal')\n",
    "axes[0].set_yticks(index  )\n",
    "axes[0].set_yticklabels(['Others','Sadness','Fear','Disgust','Anger'],fontproperties=custom_font, fontsize=35, )\n",
    "axes[0].set_title('Lexicon-based', fontsize=40, pad=12)\n",
    "axes[1].set_title('ML-based', fontsize=40, pad=12)\n",
    "axes[0].set_xticks(np.arange(0,60,10))\n",
    "axes[0].set_xticklabels(['0','10','20','30','40','50','60'], fontproperties=custom_font,fontsize=30)\n",
    "axes[1].set_xticks(np.arange(0,60,10))\n",
    "axes[1].set_xticklabels(['0','10','20','30','40','50','60'],fontweight='normal',fontproperties=custom_font,fontsize=30)\n",
    "\n",
    "for spine in axes[0].spines.values():\n",
    "    spine.set_linewidth(2.5)\n",
    "for spine in axes[1].spines.values():\n",
    "    spine.set_linewidth(2.5)\n",
    "\n",
    "# 自定义图例，使用白色框和带斜线的白色框\n",
    "legend_elements = [\n",
    "    Patch(facecolor='#2878b5', edgecolor='black', label='Objective'),\n",
    "    Patch(facecolor='#c82423', edgecolor='black', hatch='', label='Subjective'),\n",
    "   # Patch(facecolor='white', edgecolor='black', hatch='', label='Lexicon-based'),\n",
    "#    Patch(facecolor='white', edgecolor='black', hatch='/', label='ML-based')\n",
    "]\n",
    "legend = plt.legend(handles=legend_elements, frameon=True, edgecolor='black',loc=(-0.75,-0.17),ncol=2,prop=custom_font,fontsize=30,)\n",
    "legend.get_frame().set_linewidth(2.5)\n",
    "axes[0].set_xlabel('Percentage [%]', fontsize=30)\n",
    "axes[1].set_xlabel('Percentage [%]', fontsize=30)\n",
    "\n",
    "axes[1].set_xlim(0,50)\n",
    "plt.subplots_adjust(wspace=0, top=0.85, bottom=0.1, left=0.18, right=0.95)\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fec33a3-5680-401f-9aac-0cb816c3df79",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5243608d-604e-457b-b8ec-b42224f2519c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25013c41-f652-420b-b5ea-0db062e88182",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e93566e9-743d-4593-87c2-4d2bdeb64b53",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
